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Matching Code and Law: Achieving Algorithmic Fairness with Optimal
  Transport

Matching Code and Law: Achieving Algorithmic Fairness with Optimal Transport

21 December 2017
Meike Zehlike
P. Hacker
Emil Wiedemann
ArXivPDFHTML

Papers citing "Matching Code and Law: Achieving Algorithmic Fairness with Optimal Transport"

2 / 2 papers shown
Title
Review of Mathematical frameworks for Fairness in Machine Learning
Review of Mathematical frameworks for Fairness in Machine Learning
E. del Barrio
Paula Gordaliza
Jean-Michel Loubes
FaML
FedML
15
38
0
26 May 2020
Fair prediction with disparate impact: A study of bias in recidivism
  prediction instruments
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments
Alexandra Chouldechova
FaML
207
2,082
0
24 Oct 2016
1